Personality characteristics of the accident involved employee

The research relating personality traits to industrial and traffic accidents is reviewed. The research from the past 15 years is integrated with the multitude of studies preceding this period. All of the research is interpreted in terms of the differential accident liability concept, rather than the discredited accident proneness theory. The need to control for the confounding effects of age, experience, sex, and accident risk is discussed. It is concluded that the personality traits of extroversion, locus of control, impulsivity, aggression, social maladjustment, and some aspects of neurosis are related to the occurrence of accidents. Finally, the need to develop causal models of the personality-accident process and to identify causal influences through time series designs is proposed.     

Adolescent Nonsmokers,Triers, and Regular Smokers' Estimates of Cigarette Smoking Prevalence: When Do Overestimations Occur and by Whom?1

The present study tested three assumptions often made by smoking prevention researchers and practitioners regarding the nature and causes of smoking prevalence estimates. Specifically, it is often assumed that (a) adolescent prevalence estimates of all levels of smoking are inflated, (b) youths at different stages of smoking onset all overestimate smoking prevalence, and (c) the predictors of these estimates are the same for youths at different stages of smoking onset. Measures of smoking behavior based on self-reports using a bogus pipeline procedure, estimates of cigarette smoking prevalence (trying behavior and weekly use), and reports of smoking in significant others were obtained by the same youths when they were in eighth and ninth grades. Results indicated that, taken over all youths, estimates of trying cigarettes were accurate, whereas estimates of weekly use were inflated. When responders were defined by their stage of smoking onset, either as a nonsmoker, trier, or regular smoker, analyses revealed that triers were accurate regarding prevalence estimates of trying, whereas non-smokers made gross underestimations and regular smokers made overestimations of trying. All groups of youths overestimated prevalence of weekly smoking. Analyses of variance revealed that both youths' smoking status and interpersonal smoking environment additively predicted prevalence estimates, and estimates of smoking prevalence were relatively higher in youths who began to smoke, or increased their levels of smoking, within the next year. Thus, previous assumptions were partially confirmed. Future research and prevention programming should focus more on regular smoking as the focus of normative smoking distortion effects and correction efforts.     

The validity of a computerized visual searching task as an indicator of brain damage

Goldstein, Rennick, Welch, and Shelly (1973) developed a visual searching task (VST) that succeeded in obtaining a hit rate of 94.1% correct classifications when comparing brain-damaged and normal subjects and a 79.4% hit rate when comparing brain-damaged and psychiatric subjects. Goldstein and Kyc (1978) reported 92.5% correct classifications for the brain-damaged vs. normal comparisons and 82.5% correct classifications for brain-damaged vs. schizophrenic comparisons. We computerized the administration of the VST and found 85.7% correct classifications for the brain-damaged vs. normal groups and 71.4% correct classifications for the brain-damaged vs. psychiatric group. These results suggest that the computerized VST (CVST) is also a potentially valid indicator of brain damage.     

Psychosocial Predictors of Young Adolescent Cigarette Smoking: A Sixteen-Month,Three-Wave Longitudinal Study1

Understanding the psychosocial factors that predict cigarette smoking onset in young people is of crucial importance for prevention efforts. The present study examined prospective psychosocial predictors of smoking in a three-wave longitudinal data set. Similar in design to an earlier study by Chassin, Presson, Sherman, Corty, and Olshavsky (1984), the present study replicated their work, and extended it by (a) using composite predictors derived from exploratory factor analysis, (b) including prior behavior as a predictor, (c) using a design extended over three waves of data collection, and (d) using a sample composed primarily of urban teenagers. Subjects were 3295 7th-grade students at the beginning of the study. The subjects completed a questionnaire containing items tapping cigarette smoking behavior and psychosocial items that have previously been shown to predict smoking behavior. Forty-one psychosocial items on the Wave 1 (initial) questionnaire were factor analyzed, and five factors were retained. Subscale scores were constructed based on these factors and were used as predictors. Regression analyses were performed using the subscales and pretest smoking frequency to predict a continuous measure of smoking, and discriminant analyses were performed to predict transitions between qualitative levels of smoking. Prior smoking behavior was the most important predictor of future smoking. Four of the subscales, Social Disapproval, Risk Taking/Rebelliousness, Perceived Smoking Prevalence, and Motivation to Comply, were significant predictors. One subscale, Physical Consequences from Smoking, was not predictive of smoking in any of the analyses. The effect sizes cross-validated well. It is suggested that an integrative model of smoking initiation developed by Flay, d'Avernas, Best, Kersell, and Ryan (1983) best summarizes the results of the present study.